diff --git a/vllm/v1/attention/backends/mla/indexer.py b/vllm/v1/attention/backends/mla/indexer.py
index e84312970989..d94055cbe46b 100644
--- a/vllm/v1/attention/backends/mla/indexer.py
+++ b/vllm/v1/attention/backends/mla/indexer.py
@@ -1,7 +1,6 @@
 # SPDX-License-Identifier: Apache-2.0
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 from dataclasses import dataclass
-from typing import ClassVar
 
 import torch
 
@@ -25,6 +24,7 @@
     split_decodes_and_prefills,
     split_prefill_chunks,
 )
+from vllm.v1.kv_cache_interface import AttentionSpec
 from vllm.v1.worker.cp_utils import get_total_cp_world_size
 
 logger = init_logger(__name__)
@@ -202,10 +202,22 @@ def get_max_prefill_buffer_size(vllm_config: VllmConfig):
 
 
 class DeepseekV32IndexerMetadataBuilder(AttentionMetadataBuilder):
-    _cudagraph_support: ClassVar[AttentionCGSupport] = AttentionCGSupport.UNIFORM_BATCH
-
     reorder_batch_threshold: int = 1
 
+    @classmethod
+    def get_cudagraph_support(
+        cls,
+        vllm_config: VllmConfig,
+        kv_cache_spec: AttentionSpec,
+    ) -> AttentionCGSupport:
+        if not is_deep_gemm_supported():
+            logger.warning_once(
+                "DeepGEMM is not available. Disabling CUDA graph support "
+                "for sparse attention indexer. This may reduce performance.",
+            )
+            return AttentionCGSupport.NEVER
+        return AttentionCGSupport.UNIFORM_BATCH
+
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
         scheduler_config = self.vllm_config.scheduler_config